I am opening a file which has 100,000 URL's. I need to send an HTTP request to each URL and print the status code. I am using Python 2.6, and so far looked at the many confusing ways Python implements threading/concurrency. I have even looked at the python concurrence library, but cannot figure out how to write this program correctly. Has anyone come across a similar problem? I guess generally I need to know how to perform thousands of tasks in Python as fast as possible - I suppose that means 'concurrently'.
当前回答
一个使用tornado的异步网络库解决方案
from tornado import ioloop, httpclient
i = 0
def handle_request(response):
print(response.code)
global i
i -= 1
if i == 0:
ioloop.IOLoop.instance().stop()
http_client = httpclient.AsyncHTTPClient()
for url in open('urls.txt'):
i += 1
http_client.fetch(url.strip(), handle_request, method='HEAD')
ioloop.IOLoop.instance().start()
这段代码使用非阻塞网络I/O,没有任何限制。它可以扩展到数万个打开的连接。它将在单个线程中运行,但比任何线程解决方案都要快。签出非阻塞I/O
其他回答
一个解决方案:
from twisted.internet import reactor, threads
from urlparse import urlparse
import httplib
import itertools
concurrent = 200
finished=itertools.count(1)
reactor.suggestThreadPoolSize(concurrent)
def getStatus(ourl):
url = urlparse(ourl)
conn = httplib.HTTPConnection(url.netloc)
conn.request("HEAD", url.path)
res = conn.getresponse()
return res.status
def processResponse(response,url):
print response, url
processedOne()
def processError(error,url):
print "error", url#, error
processedOne()
def processedOne():
if finished.next()==added:
reactor.stop()
def addTask(url):
req = threads.deferToThread(getStatus, url)
req.addCallback(processResponse, url)
req.addErrback(processError, url)
added=0
for url in open('urllist.txt'):
added+=1
addTask(url.strip())
try:
reactor.run()
except KeyboardInterrupt:
reactor.stop()
Testtime:
[kalmi@ubi1:~] wc -l urllist.txt
10000 urllist.txt
[kalmi@ubi1:~] time python f.py > /dev/null
real 1m10.682s
user 0m16.020s
sys 0m10.330s
[kalmi@ubi1:~] head -n 6 urllist.txt
http://www.google.com
http://www.bix.hu
http://www.godaddy.com
http://www.google.com
http://www.bix.hu
http://www.godaddy.com
[kalmi@ubi1:~] python f.py | head -n 6
200 http://www.bix.hu
200 http://www.bix.hu
200 http://www.bix.hu
200 http://www.bix.hu
200 http://www.bix.hu
200 http://www.bix.hu
Pingtime:
bix.hu is ~10 ms away from me
godaddy.com: ~170 ms
google.com: ~30 ms
线程绝对不是这里的答案。它们将提供进程和内核瓶颈,以及吞吐量限制,如果总体目标是“最快的方式”,这些限制是不可接受的。
稍微扭曲一点,它的异步HTTP客户端会给你更好的结果。
自从2010年这篇文章发布以来,事情发生了很大的变化,我还没有尝试过所有其他的答案,但我尝试了一些,我发现使用python3.6对我来说这是最好的。
在AWS上运行时,我每秒可以获取大约150个独特的域名。
import concurrent.futures
import requests
import time
out = []
CONNECTIONS = 100
TIMEOUT = 5
tlds = open('../data/sample_1k.txt').read().splitlines()
urls = ['http://{}'.format(x) for x in tlds[1:]]
def load_url(url, timeout):
ans = requests.head(url, timeout=timeout)
return ans.status_code
with concurrent.futures.ThreadPoolExecutor(max_workers=CONNECTIONS) as executor:
future_to_url = (executor.submit(load_url, url, TIMEOUT) for url in urls)
time1 = time.time()
for future in concurrent.futures.as_completed(future_to_url):
try:
data = future.result()
except Exception as exc:
data = str(type(exc))
finally:
out.append(data)
print(str(len(out)),end="\r")
time2 = time.time()
print(f'Took {time2-time1:.2f} s')
一个使用tornado的异步网络库解决方案
from tornado import ioloop, httpclient
i = 0
def handle_request(response):
print(response.code)
global i
i -= 1
if i == 0:
ioloop.IOLoop.instance().stop()
http_client = httpclient.AsyncHTTPClient()
for url in open('urls.txt'):
i += 1
http_client.fetch(url.strip(), handle_request, method='HEAD')
ioloop.IOLoop.instance().start()
这段代码使用非阻塞网络I/O,没有任何限制。它可以扩展到数万个打开的连接。它将在单个线程中运行,但比任何线程解决方案都要快。签出非阻塞I/O
(工具)
Apache Bench是您所需要的全部。—用于测量HTTP web服务器性能的命令行计算机程序
给你一篇不错的博客文章:https://www.petefreitag.com/item/689.cfm(来自Pete Freitag)
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